SQLBot
Open-source ChatBI that turns natural language into SQL queries using RAG.
SQLBot is a solid open-source choice for privacy-conscious teams needing natural-language database queries. Its RAG engine and multi-turn conversation handle real-world data questions well, but you'll need a separate BI tool for polished dashboards. Best for teams already in Fit2Cloud's ecosystem (1Panel, JumpServer, DataEase) or wanting full data control. Alternatives like Tableau or Power BI offer richer visuals but are proprietary and heavier.
Verified 5d ago · liveness 46/100 · cite: rightaichoice.com/tools/sqlbot
- Data analysts
- Business users
- Small to medium-sized teams
- Open-source advocates
- Users needing advanced charting and dashboards (use Tableau/DataEase)
- Latency-sensitive real-time queries
- Non-technical users wanting zero-code simplicity
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Skip SQLBot if you need advanced interactive dashboards out of the box, require zero-code setup for non-technical users, or demand real-time sub-second query responses; for those, consider DataEase, Tableau, or Power BI instead.
Commercial support and enterprise features require contacting Fit2Cloud; you'll pay for a support contract if you need guarantees.
SQLBot is free and open source, making it the cheapest NL2SQL option for self-hosters. It costs you zero license fees, whereas proprietary alternatives like Tableau or Power BI charge per-seat subscriptions. You only pay for your own infrastructure and LLM usage. This makes SQLBot ideal for small to mid-sized teams on a budget, especially those already using Fit2Cloud's open-source stack.
In short
SQLBot — Open-source ChatBI that turns natural language into SQL queries using RAG. Best for Data analysts, Business users, Small to medium-sized teams. Free to use.
Viability Score
How well maintained and how widely used is SQLBot? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: September 2026
How we score →Key Features
- Natural language to SQL (NL2SQL)
- RAG-based context understanding with knowledge base
- Multi-turn conversational data exploration
- Built-in database connectors (MySQL, PostgreSQL)
- Audit logs and permission-based access control
- Open source, self-hosted deployment
- Knowledge base for business terms and table schemas
- Result visualization (tables, charts, export)
- Query history and feedback mechanism
- One-click deployment (1Panel)
- API for integration with external apps
- ChatBI agent for conversational data analysis
About SQLBot
SQLBot is an open-source intelligent data query system (ChatBI) developed by Fit2Cloud (Hangzhou Fit2Cloud Information Technology Co., Ltd.). It leverages large language models (LLMs) and Retrieval-Augmented Generation (RAG) to let you query databases using natural language. You can ask questions like 'How many new users per channel last week?' and get SQL-generated answers without writing code. SQLBot includes a knowledge base for business terms and table schemas, improving accuracy over multiple turns. It supports MySQL and PostgreSQL databases out of the box, provides audit logs and permission-based access control, and can be self-hosted for full data control. The latest version is v1.8, with over 250,000 downloads and 6,000+ GitHub stars. While its built-in visualization is basic, you can integrate with DataEase for advanced charts. SQLBot is free and open source, with commercial support available through Fit2Cloud.
Behind the Verdict
SQLBot shines for teams that want to democratize data access without sending sensitive data to third-party SaaS. As an open-source tool, you can self-host it and keep full control over your data, which is a major plus for regulated industries or security-conscious orgs. The RAG-based knowledge base is a differentiator: you can feed it your business terms and schema, making queries more accurate over time. Multi-turn conversation is genuinely useful for exploratory analysis. However, you'll hit limits on visualization—SQLBot returns tables and simple charts, not interactive dashboards. For that, you'll lean on DataEase or another BI tool. Setup requires some technical comfort (deployment via 1Panel or Docker), so non-technical business users won't self-serve. Also, query performance depends on your chosen LLM and hardware, so large deployments need careful planning. Overall, SQLBot is best for small to mid-size teams that value open source, privacy, and are willing to invest in knowledge base maintenance.
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Real-world workflow fit
Concrete scenarios for the personas SQLBot actually fits — and what changes day-one when you adopt it.
You need to answer ad-hoc business questions quickly without writing SQL each time.
Outcome: You connect SQLBot to your MySQL database, build a knowledge base with key business terms, and start asking questions like 'What was the retention rate for users who signed up in March?' SQLBot generates SQL, executes it, and returns a table you can export. You iterate over multiple turns, refining your ask until you
You monitor server resource usage and want to spot trends without querying logs manually.
Outcome: You connect SQLBot to your PostgreSQL metrics database and ask 'What's the average CPU usage per server over the last 7 days?' SQLBot returns a table, and you use DataEase integration to build a chart. You set up permissions so only your team can access sensitive metrics.
You need a quick KPI update without waiting for a report from your data team.
Outcome: You open the SQLBot web UI and ask 'How many new customers did we add this month compared to last?' SQLBot generates and runs the SQL, showing a comparison table. The multi-turn feature lets you drill down: 'Break it down by region.' You get answers in minutes, not days.
Use Cases
- A marketing manager asks 'How many new users each channel last week?' without writing SQL.
- An ops analyst checks server resource usage trends via natural language questions.
- A data analyst validates hypotheses quickly by conversing with the database.
- An executive asks for real-time KPI updates without waiting for reports.
- A developer integrates the SQLBot API to embed smart Q&A into a custom app.
Limitations
- The free open-source version is fully functional, but commercial support requires contacting Fit2Cloud.
- Advanced visualization is limited; complex charts and dashboards need DataEase or similar tools.
- Large-database query performance depends on your LLM and hardware.
- RAG accuracy relies on a well-maintained knowledge base.
as of 2026-08-19
Verification history
We have re-verified SQLBot 7 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
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- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
Showing the 6 most recent of 7 verification passes.
Free to cite with attribution — this page re-verifies continuously.
Where the pricing makes sense
The company stage and team size where SQLBot's pricing actually pencils out — and where peers do it cheaper.
SQLBot is free and open source, making it the cheapest NL2SQL option for self-hosters. It costs you zero license fees, whereas proprietary alternatives like Tableau or Power BI charge per-seat subscriptions. You only pay for your own infrastructure and LLM usage. This makes SQLBot ideal for small to mid-sized teams on a budget, especially those already using Fit2Cloud's open-source stack.
Setup time & first value
How long it actually takes to get something useful out of SQLBot — broken out by persona, not the marketing-page minute.
For a technical user: you can deploy SQLBot using 1Panel in about 30 minutes if you're familiar with Linux and Docker. Add 1-2 hours to configure database connections and build a basic knowledge base. Non-technical users will need help from IT; plan for half a day to get to first query.
Switching to or from SQLBot
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From Excel: You can import your data into MySQL or PostgreSQL, then use SQLBot to query it conversationally instead of pivot tables.
- →From a legacy BI tool: If you're moving from Tableau or Power BI, you can keep your database and start querying with SQLBot, though you'll lose advanced dashboards and need DataEase for visuals.
- ↗To Tableau: You can export SQLBot query results (CSV) and import into Tableau for more advanced visualization.
- ↗To DataEase: Since both are Fit2Cloud products, you can leverage SQLBot's SQL generation to feed DataEase for richer BI dashboards.
Integrations
Resources & Guides
Tutorials & Learning
Official links
Tools that pair well with SQLBot
Common stack mates teams adopt alongside SQLBot, with the specific reason each pairing earns its keep.
Chat2DB
Open-source AI SQL client that turns natural language into optimized SQL across 30+ databases, local-first and private.
Text2SQL
Turn natural language into SQL queries across major databases with schema awareness, plus a desktop app.
Hex Magic
Agentic AI analytics notebook that turns natural-language questions into governed, inspectable analyses
Featured Head-to-Head Comparisons
Sqlbot vs Screenplayiq
ScreenplayIQ is a niche tool for film-industry professionals seeking data-driven script analysis and financial forecasts, while SQLBot is a versatile open-source solution for anyone needing to query databases via natural language. Choose ScreenplayIQ for screenplay marketability insights; choose SQLBot for conversational data exploration across multiple databases. They serve completely different domains—no direct competition.
Sqlbot vs Geologicai
Choose GeologicAI if you're a mining company needing rapid, precise core scanning and AI-powered resource modeling at enterprise scale. Choose SQLBot if you're a small team wanting free, open-source, natural language querying for your databases. These tools address entirely different domains and budgets.
Sqlbot vs Nectar Energy
Nectar Energy and SQLBot serve completely different domains: Nectar focuses on automated HVAC/lighting control for commercial buildings with a new ESG reporting module (May 2026), while SQLBot is a free, open-source NL2SQL tool for data exploration. There's no direct competition—choose based on whether you need physical energy optimization or a conversational database query interface.
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